This week on High Output, Tacita Morway, CTO of Textio, reveals why the biggest challenge in the AI era isn’t learning new tools—it’s learning what not to build.

From landscape design to heavy machinery operation to leading engineering teams, Tacita’s unconventional path taught her that management isn’t about having all the answers. It’s about asking better questions. Now, as AI transforms how we build software, she’s applying that same principle to help teams navigate an overwhelming abundance of possibilities.

🎧 Subscribe and Listen Now →

What’s inside (34 min):

→ The brick wall moment. Tacita’s transition from engineer to manager felt like “running full force into a brick wall.” Her solution? Stop asking “what did I ship today?” and start asking “how are my people growing?”

→ The information fire hose problem. With AI breakthroughs arriving faster than anyone can absorb them, Tacita’s filtering strategy: problems first, technology second. “What challenges am I trying to solve right now?”

→ AI as your most honest critic. Tacita uses AI to get the unvarnished feedback her team might be too polite to give: “These systems won’t hold back—they’ll tell you when you’re missing something your colleagues might be too polite to mention.”

→ The end of rigid roles. Her prediction: role boundaries between PM, engineering manager, and designer will collapse as AI gives everyone superpowers across disciplines.

→ The focus challenge. When you can build anything quickly, staying focused on user value becomes the critical leadership skill: “You can do so much now—that’s not what they’re trying to buy right now.”

Why it matters

We’re entering an era where the constraint isn’t what we can build—it’s what we should build. As Tacita puts it: AI will “unlock creativity and invention,” but only if we resist the temptation to build everything just because we can.

The companies that win won’t be those with the fastest AI-assisted development cycles. They’ll be the ones whose leaders can cut through the noise of infinite possibilities to focus on real human problems. This requires a fundamentally different kind of engineering leadership—one that prioritizes strategic thinking over technical prowess.

Tacita’s vision of “smaller teams” and “fluid roles” isn’t about cutting headcount—it’s about unlocking organizational agility. AI enables large companies to move like small ones, where people collaborate more intensely, ideate more rapidly, and cross-pollinate ideas across dissolving role boundaries. The focus becomes what machines can’t replicate: critical thinking, user empathy, and business judgment.

Your turn

Tacita’s approach raises the essential question: In an age where you can prototype ideas in minutes and ship features in hours, how are you maintaining focus on what actually matters to your users and business?

In this age of abundance, what are you saying no to?

If you’re wrestling with these challenges, we’d love to hear your story. Schedule a chat with us → https://cal.com/team/maestro-ai/chat-with-maestro

High Output is brought to you by Maestro AI. When AI lets your team ship faster, staying focused on what matters becomes the critical leadership challenge. As your engineers become more productive, Maestro cuts through the noise with narrative status updates that digest every ticket, code change, and team discussion. Because in a world where you can build anything, you need clarity on what you’re actually building.

Visit https://getmaestro.ai to see how we help engineering leaders maintain focus in the age of abundance.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit maestroai.substack.com